TABLE 16-12 A Local Store Developed a Multiplicative Time-Series Model to Forecast

TABLE 16-12
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 2005 to 2009. The following is the resulting regression equation:
log₁₀ = 6.102 + 0.012 X - 0.129 Q₁ - 0.054 Q₂ + 0.098 Q₃
where is the estimated number of contracts in a quarter.
X is the coded quarterly value with X = 0 in the first quarter of 2005.
Q₁ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
Q₂ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
Q₃ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Table 16-12, the best interpretation of the constant 6.102 in the regression equation is

A) the fitted value for the first quarter of 2005, prior to seasonal adjustment, is log₁₀(6.102) .
B) the fitted value for the first quarter of 2005, after to seasonal adjustment, is log₁₀(6.102) .
C) the fitted value for the first quarter of 2005, prior to seasonal adjustment, is 10⁶.¹⁰².
D) the fitted value for the first quarter of 2005, after to seasonal adjustment, is 10⁶.¹⁰².